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When analyzing pharmacokinetic data, one generally employs either model fitting using nonlinear regression analysis or non-compartmental analysis techniques (NCA). The method one actually employs depends on what is required from the analysis. If the primary requirement is to determine the degree of exposure following administration of a drug (such as AUC), and perhaps the drug's associated pharmacokinetic parameters, such as clearance, elimination half-life, T (max), C (max), etc., then NCA is generally the preferred methodology to use in that it requires fewer assumptions than model-based approaches. In this chapter we cover NCA methodologies, which utilize application of the trapezoidal rule for measurements of the area under the plasma concentration-time curve. This method, which generally applies to first-order (linear) models (although it is often used to assess if a drug's pharmacokinetics are nonlinear when several dose levels are administered), has few underlying assumptions and can readily be automated.In addition, because sparse data sampling methods are often utilized in toxicokinetic (TK) studies, NCA methodology appropriate for sparse data is also discussed.

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The participatory creation of maps, above and beyond their interpretation, started in the late 1980s. At that time, development practitioners were inclined to adopt Participatory Rural Appraisal (PRA) methods such as sketch mapping (Mascarenhas et al. 1991) rather than the more complex and time consuming scale mapping. Preference was given to eliciting local knowledge and building on local dynamics to facilitate communication between insiders (e.g. villagers) and outsiders (e.g. researchers, government officials, etc.). This approach placed little emphasis on charting courses of action that would enable ordinary people to interact efficiently with policymakers (Rambaldi 2005). The situation was further compounded by state control of aerial photography, satellite imagery and large-scale topographic maps under the pretext of national security concerns.The state of affairs in mapping changed in the '90s, with the diffusion of modern spatial information technologies (including geographic information systems (GIS), global positioning systems (GPS), remote sensing image analysis software and open access to spatial data and imagery via the Internet into the industry. With the steadily decreasing cost of computer hardware and the availability of user-friendly software, spatial data that were previously controlled by government institutions became progressively more accessible 2 to, and mastered by non-governmental and community-based organisations, minority groups and sectors of society traditionally disenfranchised and excluded from spatial decision making processes (Fox et al. 2003). The new environment facilitated the integration of geo-spatial information technologies and systems (GIT&S) into community-centred initiatives. GIT practitioners and researchers around the world were able to adopt a range of GIT&S to integrate multiple realities and diverse forms of information with the objective of empowering underprivileged groups, promote social learning, support two-way communication and thereby broaden public participation across socio-economic contexts, locations and sectors. This merging of community development with geo-spatial technologies for the empowerment of less privileged communities has come to be known as Participatory Geographic Information Systems or PGIS.

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The objective of the current study was to describe and characterize the pharmacokinetics and selected pharmacodynamic effects of morphine and its two major metabolites in horses following several doses of morphine. A total of ten horses were administered a single intravenous dose of morphine: 0.05, 0.1, 0.2, or 0.5 mg/kg, or saline control. Blood samples were collected up to 72 hr, analyzed for morphine, and metabolites by LC/MS/MS, and pharmacokinetic parameters were determined. Step count, heart rate and rhythm, gastrointestinal borborygmi, fecal output, packed cell volume, and total protein were also assessed. Morphine‐3 glucuronide (M3G) was the predominant metabolite detected, with concentrations exceeding those of morphine‐6 glucuronide (M6G) at all time points. Maximal concentrations of M3G and M6G ranged from 55.1 to 504 and 6.2 to 28.4 ng/ml, respectively, across dose groups. The initial assessment of morphine pharmacokinetics was done using noncompartmental analysis (NCA). The volume of distribution at steady‐state and systemic clearance ranged from 9.40 to 16.9 L/kg and 23.3 to 32.4 ml min−1 kg−1, respectively. Adverse effects included signs of decreased gastrointestinal motility and increased central nervous excitation. There was a correlation between increasing doses of morphine, increases in M3G concentrations, and adverse effects. Findings from this study support direct administration of purified M3G and M6G to horses to better characterize the pharmacokinetics of morphine and its metabolites and to assess pharmacodynamic activity of these metabolites.

The administered dose of a drug modulates whether patients will experience optimal effectiveness, toxicity including death, or no effect at all. Dosing is particularly important for diseases and/or drugs where the drug can decrease severe morbidity or prolong life. Likewise, dosing is important where the drug can cause death or severe morbidity. Since we believe there are many examples where more precise dosing could benefit patients, it is worthwhile to consider how to prioritize drug-disease targets. One key consideration is the quality of information available from which more precise dosing recommendations can be constructed. When a new more precise dosing scheme is created and differs significantly from the approved label, it is important to consider the level of proof necessary to either change the label and/or change clinical practice. The cost and effort needed to provide this proof should also be considered in prioritizing drug-disease precision dosing targets. Although precision dosing is being promoted and has great promise, it is underutilized in many drugs and disease states. Therefore, we believe it is important to consider how more precise dosing is going to be delivered to high priority patients in a timely manner. If better dosing schemes do not change clinical practice resulting in better patient outcomes, then what is the use? This review paper discusses variables to consider when prioritizing precision dosing candidates while highlighting key examples of precision dosing that have been successfully used to improve patient care.